Spaces:
Sleeping
Sleeping
File size: 3,267 Bytes
140e059 137494b 140e059 137494b f79dad4 137494b f79dad4 4744092 f79dad4 137494b f79dad4 d84f325 140e059 d84f325 f79dad4 137494b f79dad4 137494b f79dad4 140e059 f79dad4 140e059 137494b f79dad4 137494b f79dad4 137494b f79dad4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 |
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import gradio as gr
# Load model and tokenizer
model_name = "ramsrigouthamg/t5_paraphraser"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
# Define style prompts
def generate_prompt(text, style):
style_prompts = {
"Formal": "Please rewrite the following text in a formal and professional tone:\n\n",
"Friendly": "Please rewrite the following text in a casual and friendly tone:\n\n",
"Poetic": "Rewrite the text in a poetic and metaphorical way, like a short verse:\n\n",
"Gen Z": "Rewrite this text using Gen Z slang, internet expressions, abbreviations, and emojis:\n\n"
}
# Default if style not found
base_prompt = style_prompts.get(style, "Rewrite the text:\n\n")
return base_prompt + text
# Function to rewrite text in selected style
def rewrite_text(text, style):
if not text.strip():
return "Please enter some text."
# Build the prompt based on the selected style
if style == "Gen Z":
prompt = f"Rewrite the following text in a funny Gen Z tone with slang, emojis, and internet expressions:\n\n{text}"
elif style == "Poetic":
prompt = f"Rewrite the following text in a poetic and artistic style:\n\n{text}"
elif style == "Formal":
prompt = f"Rewrite the following text in a formal, professional tone:\n\n{text}"
elif style == "Friendly":
prompt = f"Rewrite the following text in a friendly and conversational style:\n\n{text}"
else:
prompt = f"Rewrite the following text:\n\n{text}"
# Call the model (paraphraser)
response = paraphraser(prompt, max_length=100)[0]['generated_text']
# Optional: clean output (remove repeated prompt from response if needed)
return response.replace(prompt, "").strip()
# Gradio UI
import gradio as gr
# Define the interface
with gr.Blocks(theme=gr.themes.Monochrome()) as demo:
gr.Markdown(
"""
<h1 style="text-align: center;">📝 Rewrite My Text</h1>
<p style="text-align: center;">Transform your text into <b>fun, formal, poetic, or Gen Z</b> styles using AI! 🚀</p>
""",
elem_id="header",
)
with gr.Row():
with gr.Column(scale=1):
input_text = gr.Textbox(
label="Input Text",
placeholder="Enter your sentence here...",
lines=4
)
style = gr.Dropdown(
label="Choose Style",
choices=["Gen Z", "Formal", "Poetic", "Friendly"],
value="Gen Z"
)
submit_button = gr.Button("✨ Submit", variant="primary")
clear_button = gr.Button("🧹 Clear")
with gr.Column(scale=1):
output_text = gr.Textbox(
label="Rewritten Text",
placeholder="Your rewritten sentence will appear here...",
lines=4
)
# Button functionality
submit_button.click(fn=rewrite_text, inputs=[input_text, style], outputs=output_text)
clear_button.click(fn=lambda: ("", ""), inputs=[], outputs=[input_text, output_text])
# Launch the app
demo.launch(share=True)
|